Challenges for Routine Health System Data Management in a Large Public Programme to Prevent Mother-to-Child HIV Transmission in South Africa
MetadataShow full item record
CitationMate, Kedar S., Brandon Bennett, Wendy Mphatswe, Pierre Barker, and Nigel Rollins. 2009. Challenges for routine health system data management in a large public programme to prevent mother-to-child HIV transmission in South Africa. PLoS ONE 4(5): e5483.
AbstractBackground: Recent changes to South Africa's prevention of mother-to-child transmission of HIV (PMTCT) guidelines have raised hope that the national goal of reducing perinatal HIV transmission rates to less than 5% can be attained. While programmatic efforts to reach this target are underway, obtaining complete and accurate data from clinical sites to track progress presents a major challenge. We assessed the completeness and accuracy of routine PMTCT data submitted to the district health information system (DHIS) in three districts of Kwazulu-Natal province, South Africa. Methodology/Principal Findings: We surveyed the completeness and accuracy of data reported for six key PMTCT data elements between January and December 2007 from all 316 clinics and hospitals in three districts. Through visits to randomly selected sites, we reconstructed reports for the same six PMTCT data elements from clinic registers and assessed accuracy of the monthly reports previously submitted to the DHIS. Data elements were reported only 50.3% of the time and were “accurate” (i.e. within 10% of reconstructed values) 12.8% of the time. The data element “Antenatal Clients Tested for HIV” was the most accurate data element (i.e. consistent with the reconstructed value) 19.8% of the time, while “HIV PCR testing of baby born to HIV positive mother” was the least accurate with only 5.3% of clinics meeting the definition of accuracy. Conclusions/Significance: Data collected and reported in the public health system across three large, high HIV-prevalence Districts was neither complete nor accurate enough to track process performance or outcomes for PMTCT care. Systematic data evaluation can determine the magnitude of the data reporting failure and guide site-specific improvements in data management. Solutions are currently being developed and tested to improve data quality.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:4633206
- HMS Scholarly Articles